CN111524604B

CN111524604B - System for assessing ovarian reserve function of a subject

Info

Publication number: CN111524604B
Application number: CN202010265214.7A
Authority: CN
Inventors: 乔杰; 徐慧玉; 李蓉; 冯国双; 韩勇
Original assignee: Peking University Third Hospital Peking University Third Clinical Medical College
Current assignee: Guangzhou Kangrun Biotechnology Co ltd
Priority date: 2020-04-07
Filing date: 2020-04-07
Publication date: 2021-09-10
Anticipated expiration: 2040-04-07
Also published as: WO2021203450A1; CN111524604A

Abstract

The present invention relates to a system for optimized assessment of ovarian reserve function in a subject, comprising: a data acquisition module for acquiring data of the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level of the subject; and a module for calculating the ovary reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the testee.

Description

System for assessing ovarian reserve function of a subject

Technical Field

The invention relates to a system for optimized evaluation of ovarian reserve function in a subject, by means of which the condition of the ovarian reserve function of the subject itself can be evaluated, in order to evaluate the fertility potential of the subject, and to evaluate whether the fertility potential of the subject improves after a corresponding treatment.

Background

The number of primordial follicles contained in the ovarian cortex is called ovarian reserve. It reflects the ability of ovaries to provide healthy and successfully fertilized ova, and is the most important evaluation index of female ovarian function. Generally, the higher the number of primordial follicles, the better the quality, and the higher the chance of conception.

Ovarian reserve function assessment can help women of childbearing age to understand their fertility status so as to properly schedule their fertility programs. It can be used for predicting ovarian responsiveness of women of childbearing age for women with a history of infertility, and provides reference for clinical diagnosis and treatment planning of infertility. At present, the main basis for diagnosing the ovarian reserve function decline internationally and domestically is prediction of ovarian hyporesponsiveness by the blolonia standard. Thus, an index for evaluating ovarian reserve function is actually an index for predicting ovarian responsiveness.

Age factors are important factors in evaluating ovarian reserve, and one study on age and IVF success rate shows: IVF success rates are approximately 26% in women under age 30, and only 9% when aged 37 and above.

The ovarian ultrasonography comprises three aspects of detecting the number of antral follicles, the volume of ovaries and the blood flow of ovarian stroma. The antral follicle number refers to the total number of bilateral ovarian antral follicles counted by a method of transvaginal ultrasonography in the early follicular phase, and is a direct embodiment of the ovarian reserve capacity. The diameter of the antral follicle is 2-10mm or 3-8mm, the decrease of the number of antral follicles indicates poor response to ovarian stimulation, and the pregnancy rate is reduced, and researches show that the success rate of IVF prediction by the number of antral follicles is more effective than that of basic FSH detection. Ovarian stromal blood flow and ovarian volume are not currently the usual methods for predicting ovarian reactivity and assessing ovarian reserve function.

In the field of reproductive medicine, the purpose of evaluating ovarian reserve is to predict ovarian responsiveness. Currently, AMH level detection and Antral Follicle Count (AFC) are the two best internationally recognized indicators for predicting ovarian responsiveness. Basal FSH level detection is the most widely used evaluation index of ovarian reserve function internationally at present. Age factors are also important factors in assessing ovarian reserve.

Antral Follicle Count (AFC) is the number of follicles in early Gn-dependent follicular growth with a diameter of less than 8 mm. It is well known that the primordial follicle pool in the ovary is related to the number of antral follicles growing, and therefore, in theory, AFC reflects as much as possible the accuracy of the remaining ovarian follicle pool. However, to obtain good AFC results, a skilled transvaginal ultrasound (TVS) specialist is required for ultrasonography, which is both time and resource consuming. There is a lack of criteria for AFC measurement, which varies with menstrual cycle, contraceptive use, and sensitivity and resolution of TVS devices, all of which present confounders make reliable assessment of AFC more difficult.

Disclosure of Invention

In a previous patent application by the present inventors, there is provided a system for assessing ovarian reserve function in a subject, comprising: a data acquisition module for acquiring data of age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level, Antral Follicle Count (AFC) of the subject; and a module for calculating the ovary reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the testee. In this system, a cutoff point of age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level, and sinus follicle count (AFC) is detected using a Receiver Operating Characteristic (ROC) curve, and the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level, and sinus follicle count (AFC) are converted into two classification variables based on the cutoff value of the cutoff point, whereby the ovarian hypo-response probability (p) of the subject is calculated using the two classification variables as prediction variables.

The system can effectively calculate the probability of low ovarian response of the testee, and further, default ovarian reserve function grouping parameters are prestored in a grouping module included in the system, and the ovarian low response probability p calculated by the system is grouped according to the grouping parameters, so that the ovarian reserve level of the testee can be grouped.

Using a system developed by the inventors herein before for assessing the function of ovarian reserve in a subject, the probability of hyporesponsiveness of the ovary in the subject can be calculated and the ovarian reserve levels of the subject can be further grouped according to the probability of hyporesponsiveness of the ovary. The system can be used for calculating a parameter (p) for predicting the low response probability of the ovary of the subject, and grouping the ovary reserve function of the subject according to a default ovary reserve function grouping parameter prestored in the system, so as to judge the level of the ovary reserve function and evaluate the ovary reserve level.

Despite the development of the above system, because sinus follicle count (AFC) requires a transvaginal ultrasound probed approach to count the total number of bilateral ovarian antral follicles, is difficult to obtain, causes some harm to the subject, is difficult to sample compared to age, and to the AMH and FSH levels available by blood draw, and with the recent development of AMH kits, there is an increasing suggestion to use AMH instead of AFC to assess ovarian reserve due to the complexity, cost and variability between the person performing the AFC test. Therefore, there is a need in the art to develop further new systems that allow for simpler and more convenient detection data to accurately predict ovarian reserve function in a subject.

As described above, judging the ovarian reserve function of a subject is a very important task for a clinician or the like. By assessing ovarian reserve function, one can predict ovarian responsiveness in patients, an important clinical outcome during ovulation-promoting therapy. In the past, clinicians usually combine their own experiences to judge according to age, body mass index, endocrine factor level, antral follicle number and the like, and have certain subjectivity. Our system can accurately assess the functional condition of ovarian reserve for a subject to be treated, so as to assist a clinician in making a more targeted treatment plan in subsequent treatments.

In conclusion, it is known that the determinant of ovarian responsiveness is ovarian reserve function, but the inventors of the present application thought in reverse to evaluate ovarian reserve function with expected ovarian responsiveness. In addition, for a patient receiving infertility treatment, from a clinical perspective, ovarian responsiveness is related to ovulation-promoting agent amount in addition to basic conditions (age, basal FSH level, and AMH level) of the patient, and the inventor of the present application firstly obtains an expected low ovarian response probability according to the basic conditions of the patient, and then groups the ovarian reserve functions of the subject according to default ovarian reserve function grouping parameters prestored by the system, thereby judging the level of the ovarian reserve functions of the subject, and evaluating the ovarian reserve levels.

In particular, the invention relates to the following:

1. a system for assessing ovarian reserve function in a subject, comprising:

a data acquisition module for acquiring data of the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level of the subject; and

and a module for calculating the ovarian reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the subject.

2. The system of item 1, further comprising:

and the grouping module is prestored with a default ovarian reserve function grouping parameter and groups the calculated low ovarian response probability p according to the grouping parameter, so as to group the ovarian reserve level of the subject.

3. The system of item 1 or 2, wherein,

in the module for calculating ovarian reserve function, the ovarian hypo-response probability (p) of the subject is calculated using a multi-categorical variable into which data on the subject's age, subject's anti-mullerian hormone (AMH) level, and subject's Follicle Stimulating Hormone (FSH) level are converted.

4. The system of item 3, wherein,

the anti-mullerian hormone (AMH) level is the concentration of anti-mullerian hormone in venous blood of any day of the menstrual cycle of the female subject, and the Follicle Stimulating Hormone (FSH) level is the concentration of follicle stimulating hormone in venous blood of the female subject from 2 to 4 days of menstruation.

5. The system of item 3 or 4, wherein,

in the module for calculating ovarian reserve function, the age of the subject is converted into three classification variables,

the age of the subject was divided into three groups, respectively: the subject is aged 30 years and below, the subject is aged greater than 30 years and 40 years and below, and the subject is aged greater than 40 years.

6. The system according to any one of items 3 to 5, wherein,

in a module for calculating ovarian reserve function, the anti-mullerian hormone (AMH) level of a subject is converted into five categorical variables,

the subjects' anti-mullerian hormone (AMH) levels were divided into five groups, each: the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, the subject's anti-mullerian hormone (AMH) level is from 0.5ng/ml and above to less than 1ng/ml, the subject's anti-mullerian hormone (AMH) level is from 1ng/ml and above to less than 1.5ng/ml, the subject's anti-mullerian hormone (AMH) level is from 1.5ng/ml and above to less than 2ng/ml, and the subject's anti-mullerian hormone (AMH) level is at least 2 ng/ml.

7. The system according to any one of items 3 to 6, wherein,

in a module for calculating ovarian reserve function, converting the subject's Follicle Stimulating Hormone (FSH) level to a four-categorical variable,

the subject's Follicle Stimulating Hormone (FSH) levels were divided into four groups, each: the subject's Follicle Stimulating Hormone (FSH) level is less than 6.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is more than 6.5 and IU/L and less than 8.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is more than 8.5IU/L and less than 10.5IU/L, and the subject's Follicle Stimulating Hormone (FSH) level is more than 10.5 IU/L.

8. The system according to any one of items 1 to 7, wherein,

the module for calculating the ovarian reserve function stores in advance a formula for predicting the ovarian hypo-response probability (p) of a subject, which is fitted based on multi-classification variables into which data of the subject's subject age, the subject's anti-mullerian hormone (AMH) level, and the subject's Follicle Stimulating Hormone (FSH) level are converted in an existing database.

9. The system of item 8, wherein,

the formula is the following formula one:

p ^ 1/(1+ e ^ (a + b ^ age + c ^ FSH + d ^ AMH))) (formula I)

Wherein p is a parameter calculated to characterize ovarian reserve function in the subject,

wherein a, b, c and d are unitless parameters;

wherein, in the module for calculating ovarian reserve function, values of b, c and d are obtained based on the age of the subject, the anti-mullerian hormone (AMH) level of the subject and the Follicle Stimulating Hormone (FSH) level of the subject to be substituted into formula one for calculation, wherein in the calculation, the values of age, FSH and AMH are 0 or 1.

10. The system of item 9, wherein,

a is any value selected from-4.072 to-3.188, and a is preferably-3.630;

when the subject is aged 30 years and below, age is 0,

when the subject is older than 30 years and 40 years and younger, age is 1, b is any number selected from 0.163 to 0.960, b is preferably 0.561, and

when the subject is older than 40 years, age is 1, b is any value selected from 0.295-1.317, and b is preferably 0.806;

when the subject has a Follicle Stimulating Hormone (FSH) level of less than 6.5IU/L, the FSH is 0,

when the subject has a Follicle Stimulating Hormone (FSH) level of 6.5IU/L or more and less than 8.5IU/L, FSH is 1, c is any value selected from 0.239 to 1.006, c is preferably 0.622,

when the subject has a Follicle Stimulating Hormone (FSH) level of 8.5IU/L or more and less than 10.5IU/L, FSH is 1, c is any value selected from 0.363 to 1.303, c is preferably 0.833, and

when the subject has a Follicle Stimulating Hormone (FSH) level of 10.5IU/L or more, FSH is 1, c is any value selected from 0.847-1.712, and c is preferably 1.279;

when the subject's anti-mullerian hormone (AMH) level is 2ng/ml and above, AMH is 0;

when the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, AMH is 1, d is any value selected from 2.708-3.701, d is preferably 3.204,

when the subject's anti-mullerian hormone (AMH) level is 0.5ng/ml or more and less than 1ng/ml, AMH is 1, d is any value selected from 1.985-2.887, d is preferably 2.436,

when the subject's anti-mullerian hormone (AMH) level is 1ng/ml or more and less than 1.5ng/ml, AMH is 1, d is any value selected from 1.153 to 2.070, d is preferably 1.612,

when the subject's anti-mullerian hormone (AMH) level is 1.5ng/ml or more and less than 2ng/ml, AMH is 1, d is any value selected from 0.230-1.356, d is preferably 0.793.

11. The system according to any one of items 2 to 10, wherein,

the grouping basis prestored in the grouping module is as follows:

when the calculated probability of ovarian hypo-response (p) for the predictive subject is < 10%, the grouping module determines that the subject belongs to ovarian reserve functional;

when the calculated ovarian hypo-reaction probability (p) of the test subject is less than 25 percent and is less than 10 percent, the grouping module determines that the test subject has better ovarian reserve function;

when the calculated ovarian hypo-response probability (p) of the test subject is less than 50 percent and is less than 25 percent, the grouping module determines that the test subject belongs to poor ovarian reserve function;

when the calculated probability (p) of ovarian hypo-reaction for predicting the subject is more than or equal to 50%, the grouping module determines that the subject belongs to poor ovarian reserve function.

12. A method for assessing ovarian reserve function in a subject, comprising:

a data acquisition step of acquiring data of the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level of the subject; and

and a step of calculating the ovarian reserve function by performing a calculation using the information obtained in the data collection step, thereby calculating the probability (p) of hyporesponsiveness of the ovary of the subject.

13. The method of item 12, further comprising:

a grouping step, wherein a pre-known ovarian reserve function grouping parameter is utilized in the grouping step, and the calculated low ovarian response probability p is grouped according to the grouping parameter, so that the ovarian reserve level of the subject is grouped.

14. The method of item 12 or 13, wherein,

in the step of calculating the ovarian reserve function, the ovarian hypo-response probability (p) of the subject is calculated using a multi-categorical variable into which data on the age of the subject, the anti-mullerian hormone (AMH) level of the subject, and the Follicle Stimulating Hormone (FSH) level of the subject are converted.

15. The method of item 14, wherein,

16. The method of item 14 or 15, wherein,

in the step of calculating ovarian reserve function, the age of the subject is converted into a three-classification variable,

17. The method according to any one of items 14 to 16, wherein,

in the step of calculating ovarian reserve function, the subject's anti-mullerian hormone (AMH) level is converted into five categorical variables,

18. The method according to any one of items 14 to 17, wherein,

in the step of calculating ovarian reserve function, converting the subject's Follicle Stimulating Hormone (FSH) level to a four-categorical variable,

19. The method according to any one of items 11 to 18, wherein,

in the step of calculating ovarian reserve function, a formula for predicting the ovarian hypo-response probability (p) of the subject is fitted based on multi-categorical variables into which data of the subject's subject age, subject anti-mullerian hormone (AMH) level, and subject Follicle Stimulating Hormone (FSH) level are converted in the existing database.

20. The method of item 19, wherein,

the formula is the following formula one:

p ^ 1/(1+ e ^ (a + b ^ age + c ^ FSH + d ^ AMH))) (formula I)

wherein a, b, c and d are unitless parameters;

wherein, in the step of calculating the ovarian reserve function, values of b, c and d are obtained based on the age of the subject, the anti-mullerian hormone (AMH) level of the subject, and the Follicle Stimulating Hormone (FSH) level of the subject to be substituted into formula one for calculation, and in the calculation, the values of age, FSH, and AMH are 0 or 1.

21. The method of item 20, wherein,

a is any value selected from-4.072 to-3.188, and a is preferably-3.630;

when the subject is aged 30 years and below, age is 0,

22. The method according to any one of items 12 to 21, wherein,

the grouping used in the grouping step is based on:

Effects of the invention

The ovarian reserve is the most main reason for the reduction of the female fertility, but the individual difference of the ovarian reserve is large, and some people are at risk of reducing the ovarian reserve and even exhausting the ovarian reserve in a mild year grade, so that the ovarian reserve is very necessary to be evaluated in time. Ovarian reserve function assessment can help women of childbearing age to understand their fertility status so as to properly schedule their fertility programs. It can be used for predicting ovarian responsiveness of women of childbearing age for women with a history of infertility, and provides reference for clinical diagnosis and treatment planning of infertility. At present, the diagnosis of ovarian hyporesponsiveness by the blolonia standard is mainly used for diagnosing the ovarian hyporesponsiveness at home and abroad. Thus, an index for evaluating ovarian reserve function is actually an index for predicting ovarian responsiveness.

Specifically, in the present invention, the ovarian hypo-response probability of the subject can be calculated by using the system for evaluating the ovarian reserve function of the subject, so that the ovarian reserve level of the subject is grouped according to the ovarian hypo-response probability. By utilizing the system, the parameter (p) for predicting the low ovarian response probability of the testee can be calculated, and the ovarian reserve functions of the testee are grouped according to the default ovarian reserve function grouping parameter prestored by the system, so that the level of the ovarian reserve functions is judged, and the ovarian reserve level can be evaluated.

The inventor of the application realizes that the ovarian reactivity is closely related to the ovarian reserve, the poorer the ovarian reserve function is, the higher the risk of ovarian hypo-response is, and whether the ovarian hypo-response is high risk is frequently used clinically to evaluate the ovarian reserve function reduction. The ovarian reserve is in the order of high to low, i.e. the ovarian hypo-reactive probability is in the order of low to high.

By utilizing the system and the method, the quality of the ovarian reserve function of the testee to be treated can be accurately evaluated, and a more targeted treatment scheme can be prepared by a clinician in the subsequent treatment. The method can help general women of child bearing age, especially women of child bearing age who want to bear the child but are uncertain about when to bear the child, to evaluate the ovarian reserve function of the women, and to make a reasonable birth plan.

The inventor of the invention firstly uses three indexes of serum AMH level on any day of menstrual cycle, age and serum FSH level on 2-4 days of menstrual cycle to evaluate the function of ovarian reserve. Compared with the prior system, the Antral Follicle Counting (AFC) counted by the method of vaginal ultrasonography can be omitted, but the accuracy can still reach the level of the prior system, and in addition, the detection cost can be reduced because the Antral Follicle Counting (AFC) does not need to be detected. In addition, the factors influencing the AFC detection result are more, compared with AFC, the accuracy and repeatability of FSH and AMH results are better, and the effect similar to that of a four-index system can be achieved by using the three-index system.

The system and the method can quickly and accurately evaluate the ovarian reserve level of the testee, and solve the problems of poor repeatability and non-uniform standard caused by evaluating the ovarian reserve function mainly according to the experience of doctors and some simple cut-off values of ovarian reserve indexes in the prior art.

Detailed Description

Specific embodiments of the present invention will be described in more detail below. It should be understood, however, that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

It should be noted that certain terms are used throughout the description and claims to refer to particular components. As one skilled in the art will appreciate, various names may be used to refer to a component. This specification and claims do not intend to distinguish between components that differ in name but not function. In the following description and in the claims, the terms "include" and "comprise" are used in an open-ended fashion, and thus should be interpreted to mean "include, but not limited to. The description which follows is a preferred embodiment of the invention, but is made for the purpose of illustrating the general principles of the invention and not for the purpose of limiting the scope of the invention. The scope of the present invention is defined by the appended claims.

Reference herein to ovarian reserve is to: the number of primordial follicles contained in the ovarian cortex is called ovarian reserve. It reflects the ability of ovaries to provide healthy and successfully fertilized ova, and is the most important evaluation index of female ovarian function. Generally, the higher the number of primordial follicles, the better the quality, and the higher the chance of conception.

However, primordial follicle count cannot be evaluated non-invasively, and can only be evaluated by the number of follicles mobilized per menstrual cycle, whereas fewer follicles mobilized during the IVF-ET cycle (hypo-response of the ovaries) suggests a decreased ovarian reserve function.

Age factors are generally considered to be the most important factor in assessing ovarian reserve, and one study of age and IVF success rate shows: IVF success rates are approximately 26% in women under age 30, and only 9% when aged 37 and above.

The mechanism by which ovarian reserve capacity decreases with age is as follows. The number of follicles decreases and primordial follicles appear after the sex differentiation of the embryo, when the number of follicles is at its maximum, after puberty the follicles begin to develop and mature, and the unopened follicles, which are recruited as ovulation completes, disappear to form the corpus luteum. The number of follicles decreases with age: in humans, 20-week-old embryos are the largest, about 600 ten thousand follicles, the neonatal period is reduced to 70-200 ten thousand, the adolescence period is about 4 ten thousand, and only more than one thousand are left at the beginning of the menopause period until the complete exhaustion. And (II) the quality of the ovum is reduced, the embryo quality is mainly determined by the quality of the ovum, the probability of the aneuploidy of the ovum is increased, the risk of the abnormal function of mitochondria is increased, the polarity of the ovum is lost, and the epigenetic change of the ovum is caused by the old age. Endocrine factors, the hypothalamic-pituitary-ovarian axis, regulate the menstrual cycle and ovulation in women, and abnormal endocrine levels in this axis lead to infertility. AMH and inhibin B are secreted by small follicles, and are directly reflected in the reserve capacity of the ovary. As ovarian reserve decreases with age, the number of recruitable follicles decreases, and consequently their secreted AMH and inhibin B concentrations also decrease. Inhibin B negatively feeds back to regulate pituitary FSH secretion, and decreased Inhibin B levels lead to increased luteal FSH secretion. Increasing FSH prematurely promotes the growth and secretion of new follicles and E2, ultimately shortening the menstrual cycle. Increased serum FSH levels, decreased inhibin B levels, and decreased sensitivity of the follicles to FSH suggest a decrease in the number of antral follicles that can be recruited. The menstrual cycle is the manifestation of ovarian reserve and fertility, and the shortening of the menstrual cycle due to aging, and the reduction of the menstrual cycle for 2-3 days is a sensitive indication of the aging of the reproductive system, and indicates that follicle growth is started early (FSH level is increased) and primordial follicle reserve is reduced.

Continuous variables: in statistics, variables can be classified into continuous variables and classified variables according to whether the variable values are continuous or not. The variable which can be arbitrarily valued in a certain interval is called continuous variable, the numerical value is continuous, and two adjacent numerical values can be infinitely divided, i.e. an infinite number of numerical values can be obtained. For example, the specification size of the produced part, the height, weight, chest circumference and the like measured by a human body are continuous variables, and the numerical values can be obtained only by a measuring or metering method. Conversely, values that can only be calculated in natural or integer units are discrete variables. For example, the number of businesses, employees, equipment, etc. can only be counted in units of a meter, and the value of such variables is typically obtained by a counting method.

Categorical variables refer to variables in terms of geographic location, demographics, etc., which function to group survey respondents. The description variables describe the difference between a certain customer group and other customer groups. Most categorical variables are also descriptive variables. Categorical variables can be divided into two broad categories, unordered categorical variables and ordered categorical variables. Wherein, unordered categorical variable (unordered categorical variable) refers to the degree and order of difference between the categories or attributes being classified. It can be classified into two categories, such as sex (male and female), drug reaction (negative and positive), etc.; ② a plurality of classifications, such as blood type (O, A, B, AB), occupation (worker, agriculture, business, school, soldier), etc. And there is a degree of difference between the categories of the ordered categorical variable (the ordered categorical variable). For example, the urine glucose assay results are classified according to-, + +; the curative effects are classified according to cure, obvious effect, improvement and ineffectiveness. For the ordered classification variables, the variables are firstly grouped according to the grade sequence, the number of observation units of each group is counted, a frequency table of the ordered variables (each grade) is compiled, and the obtained data is called grade data.

The variable types are not invariable and conversion between the various types of variables is possible depending on the needs of the study. For example, the hemoglobin (g/L) is a primary numerical variable, and if the hemoglobin is divided into two categories according to the normal hemoglobin and the low hemoglobin, the two categories can be analyzed according to the two categories; if the blood is classified into five grades according to severe anemia, moderate anemia, mild anemia, normal and hemoglobin increase, the analysis can be performed according to grade data. The classifier data may also be quantified, e.g., the patient's nausea response may be expressed as 0, 1, 2, 3, and may be analyzed as numerical variable data (quantitative data).

The present invention relates to a system for assessing ovarian reserve function in a subject, comprising:

a data acquisition module for acquiring data of the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level of the subject; and a module for calculating the ovary reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the testee.

The present invention also relates to a system for assessing ovarian reserve function in a subject, comprising:

a module for calculating ovarian reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the testee; and the grouping module is prestored with a default ovarian reserve function grouping parameter and groups the calculated low ovarian response probability p according to the grouping parameter, so as to group the ovarian reserve level of the subject.

Anti-mullerian hormone (AMH) is a hormone secreted by the granulosa cells of ovarian small follicles, and female babies at fetal stage make AMH from 9 months of stool, and the higher the number of small follicles in the ovaries, the higher the concentration of AMH; on the contrary, when the follicles are gradually consumed with age and various factors, the AMH concentration is also decreased, and the closer to the menopause, the AMH tends to be 0.

Follicle Stimulating Hormone (FSH) is a hormone secreted by anterior pituitary basophils and is composed of glycoproteins, which primarily function to promote follicular maturation. FSH promotes proliferative differentiation of follicular granular layer cells and promotes overall ovarian growth. And acting on the seminal tubules of testis to promote spermatogenesis. FSH is secreted in humans in pulses, and in women varies with the menstrual cycle. The determination of FSH in serum has important significance for diagnosing and treating infertility and endocrine diseases, such as understanding pituitary endocrine function, indirectly understanding ovarian functional state, evaluating ovarian reserve and ovarian reactivity, and making ovulation-promoting drug dosage.

In the present invention, the anti-mullerian hormone (AMH) level is the concentration of anti-mullerian hormone in a venous blood serum sample taken at any day of the subject's menstrual cycle, and the Follicle Stimulating Hormone (FSH) level is the concentration of follicle stimulating hormone in a venous blood serum sample taken at 2-4 days of the female subject's menstrual cycle.

In the module for calculating ovarian reserve function, the inventors of the present application conducted intensive studies to convert the age of a subject into three categorical variables, i.e., the age is divided into three groups, respectively: the subject is under 30 years of age, the subject is above 30 years of age and under 40 years of age, and the subject is above 40 years of age.

In the module for calculating ovarian reserve function, the inventors of the present application underwent intensive studies to convert the anti-mullerian hormone (AMH) levels of subjects into five categorical variables, i.e., dividing the anti-mullerian hormone (AMH) levels into five groups, respectively: (ii) an anti-mullerian hormone (AMH) level of less than 0.5ng/ml in the subject, an anti-mullerian hormone (AMH) level of greater than 0.5ng/ml and less than 1ng/ml in the subject, an anti-mullerian hormone (AMH) level of greater than 1ng/ml and less than 1.5ng/ml in the subject, an anti-mullerian hormone (AMH) level of greater than 1.5ng/ml and less than 2ng/ml in the subject, and an anti-mullerian hormone (AMH) level of greater than 2ng/ml in the subject;

in the module for calculating ovarian reserve function, the inventors of the present application have conducted intensive studies to convert the subject's Follicle Stimulating Hormone (FSH) level into four categorical variables, i.e., to divide the Follicle Stimulating Hormone (FSH) level into four groups, respectively: the subject's Follicle Stimulating Hormone (FSH) level is less than 6.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is more than 6.5IU/L and less than 8.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is more than 8.5IU/L and less than 10.5IU/L, and the subject's Follicle Stimulating Hormone (FSH) level is more than 10.5 IU/L.

In the module for calculating ovarian reserve function, the applicant of the present application has conducted elaborate studies by dividing the age of a subject into three categorical variables, dividing the anti-mullerian hormone (AMH) level into five categorical variables, and dividing the Follicle Stimulating Hormone (FSH) level into four categorical variables as described above, thereby achieving the effects of changing continuous variables into different multi-categorical variables, substituting into a categorical variable model, calculating the ovarian hypo-response probability, and grouping the ovarian reserve functions according to the grouping principle summarized by the inventor of the present application to obtain the ovarian reserve function status of the subject.

By transforming the 3 variables into different multi-categorical variables, data analysis using such multi-categorical variables can more accurately predict ovarian reserve function of a subject with better model stability. In the present application, a system for predicting ovarian reserve was constructed using three indices of age, anti-mullerian hormone (AMH) level and Follicle Stimulating Hormone (FSH) level, instead of the system for predicting ovarian reserve which was originally constructed using four indices of age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level and sinus follicle count (AFC). Although the four-index system is very effective in prediction, if the Antral Follicle Count (AFC) data can be avoided, the operability of the system is further improved and the cost of running the whole system is reduced. In addition, the correlation in the original four-variable model is strong, and the functions of the indexes are overlapped. The inventors of the present application therefore made elaborate work in this application to remove the sinus follicle count (AFC) index that is more difficult to obtain, and to classify other indices more finely instead of the two classification variables before. Through a large number of attempts and continuous improvement of the system, according to the classification basis described in the application, instead of adopting a mode of completely converting the classification basis into two classification variables, the age is converted into three classification variables, meanwhile, the classification standard is optimized, the anti-mullerian hormone (AMH) level is converted into five classification variables, meanwhile, the classification standard is optimized, the Follicle Stimulating Hormone (FSH) level is converted into four classification variables, and meanwhile, the classification standard is optimized, so that the original four-index system is replaced by three indexes, and the same good prediction effect is realized.

By accurately evaluating the ovarian reserve function of the subject, the system can help a clinician to formulate a more effective scheme and more accurately evaluate whether the treatment scheme can effectively improve the ovarian reserve function of the subject after the subject receives treatment for a period of time.

The module for calculating the ovarian reserve function stores in advance a formula for predicting the ovarian hypo-response probability (p) of a subject, which is fitted based on multi-classification variables into which data of the subject's subject age, the subject's anti-mullerian hormone (AMH) level, and the subject's Follicle Stimulating Hormone (FSH) level are converted in an existing database. And grouping the ovarian reserve function condition of the testee according to grouping standards.

In the present invention, the existing database refers to a database composed of subjects who are currently receiving treatment or who have previously received treatment and meet the following inclusion and exclusion criteria, and there is no provision for the sample size of the database, but the larger the sample size of the database is, the better the sample size is, for example, 100 subjects, 200 subjects, 300 subjects, preferably 400 subjects or more, and more preferably 500 subjects or more. In one particular embodiment, an existing database of 1523 samples is employed. In one particular embodiment, an existing database of 3273 samples was used.

The inclusion and exclusion criteria are, respectively, the inclusion criteria: women aged 20-45 years have a Body Mass Index (BMI) of less than or equal to 30, six consecutive menstrual cycles of 25-45 days, and normal bilateral ovarian morphology is assessed by vaginal ultrasonography, i.e., the number of IVF/ICSI-ET cycles is less than or equal to 2. Exclusion criteria were: hydrosalpinx, unilateral ovarian AFC >20, polycystic ovarian syndrome, other untreated metabolic or endocrine diseases, previous surgery on the ovary or uterine cavity, intrauterine abnormalities, within 3 months of pregnancy, smoking, couples who have previously undergone radiotherapy or chemotherapy with oral contraceptives or other hormones within the previous two months, and who have previously undergone genetic diagnosis for PGD (preimplantation embryonic genetic diagnosis)/PGS (preimplantation genetic screening) treatment.

In selecting a sample of the database, subjects capable of inclusion in the database need to meet both the inclusion and exclusion criteria described above.

The module for calculating ovarian reserve function calculates a parameter (p) for characterizing ovarian reserve function of the subject from the data acquired in the data acquisition module using the formula:

p ^ 1/(1+ e ^ (a + b ^ age + c ^ FSH + d ^ AMH))) (formula I)

wherein a, b, c and d are unitless parameters;

Further, a is any value selected from-4.072 to-3.188, and a is preferably-3.630; age is 0 when the subject is at age 30 years and below, age is 1 when the subject is at age greater than 30 years and at age 40 years and below, b is any number selected from 0.163-0.960, b is preferably 0.561, and when the subject is at age greater than 40 years, age is 1, b is any number selected from 0.295-1.317, b is preferably 0.806; the FSH is 0 when a Follicle Stimulating Hormone (FSH) level of the subject is less than 6.5IU/L, the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 6.5IU/L or more and less than 8.5IU/L, c is any value selected from 0.239 to 1.006, c is preferably 0.622, the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 8.5IU/L or more and less than 10.5IU/L, c is any value selected from 0.363 to 1.303, c is preferably 0.833, and the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 10.5IU/L or more, c is any value selected from 0.847 to 1.712, c is preferably 1.279. When the subject's anti-mullerian hormone (AMH) level is 2ng/ml and above, AMH is 0; when the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, AMH is 1, d is any value selected from 2.708-3.701, d is preferably 3.204, when the subject's anti-mullerian hormone (AMH) level is 0.5ng/ml and above and less than 1ng/ml, AMH is 1, d is any value selected from 1.985-2.887, d is preferably 2.436, when the subject's anti-mullerian hormone (AMH) level is 1ng/ml and above and less than 1.5ng/ml, AMH is 1, d is any value selected from 1.153-2.070, d is preferably 1.612, when the subject's anti-mullerian hormone (AMH) level is 1.5ng/ml and above and less than 2ng/ml, AMH is 1, d is any value selected from 0.230-1.356, d is preferably 0.793.

The grouping module of the application is pre-stored with the evaluation and grouping basis of the ovary reserve function. When the calculated parameter (p) for characterizing the ovarian hypo-reactivity probability of the subject is < 10%, the grouping module determines that the subject belongs to ovarian reserve functional; when the calculated parameter (p) for representing the ovarian hypo-response probability of the subject is less than 25 percent and is less than 10 percent, the grouping module determines that the subject belongs to the ovarian reserve function better; when 20% ≦ calculated parameter (p) for characterizing ovarian hypo-response probability of the subject < 50%, the grouping module determines that the subject is a poorly functioning ovarian reserve; when the calculated parameter (p) for representing the low ovarian response probability of the subject is more than or equal to 50 percent, the grouping module determines that the subject belongs to poor ovarian reserve function.

In another specific embodiment of the present application, the present application further relates to a method for assessing ovarian reserve function in a subject, the method comprising a data acquisition step of acquiring data on the age, anti-mullerian hormone (AMH) level, Follicle Stimulating Hormone (FSH) level of the subject; and a step of calculating an ovarian reserve function by performing a calculation using the information acquired in the data acquisition step, thereby calculating a probability (p) of low ovarian response of the subject. In addition, the method further comprises: a grouping step, wherein a pre-known ovarian reserve function grouping parameter is utilized in the grouping step, and the calculated low ovarian response probability p is grouped according to the grouping parameter, so that the ovarian reserve level of the subject is grouped.

As described above, the specific contents of the steps performed in the method of the present application, the acquisition, grouping and processing of data on the age of the subject, the anti-mullerian hormone (AMH) level of the subject and the Follicle Stimulating Hormone (FSH) level of the subject, can be performed with reference to the respective modules of the system of the present application.

Examples

In the examples, a sample size estimation was first performed, the total sample size being >553, all couples struggling to attempt pregnancy for at least 12 months.

The study was conducted on couples for total inclusion 561 by three centers of reproductive medicine according to the inclusion and exclusion criteria described below, i.e. 561 pairs of couples meeting the inclusion and exclusion criteria described below were selected for subsequent study.

The inclusion criteria were: women aged 20-45 years have a Body Mass Index (BMI) of less than or equal to 30, six consecutive menstrual cycles of 25-45 days, and normal bilateral ovarian morphology is assessed by vaginal ultrasonography, i.e., the number of IVF/ICSI-ET cycles is less than or equal to 2.

Exclusion criteria were: hydrosalpinx, unilateral ovarian AFC >20, polycystic ovarian syndrome, other untreated metabolic or endocrine diseases, previous surgery on the ovary or uterine cavity, intrauterine abnormalities, within 3 months of pregnancy, smoking, couples who have previously undergone radiotherapy or chemotherapy with oral contraceptives or other hormones within the previous two months, and who have previously undergone genetic diagnosis for PGD (preimplantation embryonic genetic diagnosis)/PGS (preimplantation genetic screening) treatment.

Controlled Ovarian Stimulation (COS) treatment

Gn (i.e. human recombinant FSH) treatment was initiated on day 2 or day 3 of the menstrual cycle. The initial dose is selected based on age, BMI (i.e., body Mass index, which is a number obtained by dividing kilograms of body weight by meters of height squared, and is a current international standard for measuring the degree of obesity and health of a human), FSH and AFC levels over 2-4 days per month. During ovulation induction, the Gn initial dose is based on ultrasound observation and serum E₂Level to adjust. GnRH antagonist treatment starts on day 5-7 of stimulation when the growing follicle is 10-12mm in diameter. When at least 2 dominant follicles (> 18mm in diameter) were visible by ultrasound, 5000-. Ova were removed 36 hours after hCG administration. Transferring 1-3 embryos or performing embryo cryopreservation. Then, a luteinizing progesterone support is provided.

In the examples of the present application, subjects treated with the GnRH antagonist described above were received between 2017 and 2018 by the applicant of the present application, wherein finally 1523 subjects in 2017 had their data according to the above criteria and 3273 subjects in 2018 had their data according to the above criteria. For constructing the system to which the present application relates.

Sample acquisition and endocrine determination

For 4796 subjects as described above, venous blood samples were drawn and immediately inverted five times to promote complete blood clotting, and serum was collected by centrifugation and used for endocrine assessment. Measuring the subject's Follicle Stimulating Hormone (FSH) level on day 2 of the subject's menstrual cycle, and measuring the subject's anti-mullerian hormone (AMH) level on any day of the subject's menstrual cycle. FSH measurements of serum were performed using the siemens Immulite 2000 immunoassay system (siemens medical diagnostics, ltd., shanghai, china). Quality Control of the FSH assay was provided by Bio-RAD laboratories (Lyphonek Immunolay Plus Control, Trilevel, Cat. No. 370, batch No. 40340). Serum AMH concentrations of subjects were measured using an ultrasensitive two-point ELISA kit (Ansh Labs, usa).

In this example, the Follicle Stimulating Hormone (FSH) level at 2-4 days of menstruation refers to the follicle stimulating hormone level detected in a venous blood serum sample of a female subject who is in the second to fourth days of the menstruation period. AMH levels at any day of the menstrual cycle refer to anti-mullerian hormone levels measured from venous blood serum samples from female subjects on any day during the menstrual period. The data for the system used to build the model is shown in table 1 below.

TABLE 1 clinical and biochemical data for subjects treated with GnRH antagonists

	2017(n＝1523)	2018(n＝3273)
			Average age (year of age)	33.4±5.3	32.7±4.8
Mean FSH (IU/L)	7.5±3.3	7.2±3.1
			Average AMH (ng/ml)	2.2(1.1-4.0)	2.7(1.2-4.8)

System model construction

In this example, 4796 subjects with poor ovarian response and less than 5 (specifically 0, 1, 2, 3, or 4) oocytes from the subjects were defined as outcome variables and the predictor variables were age, FSH level, and AMH level. In the embodiment, the prediction model is constructed by using 2017 data, namely 1523 subjects data to initially construct the model system of the application, and 2018 data, namely 3273 subjects data to verify the effect of the system model.

The specific steps are that JMP Pro 14.2 software is utilized, multi-factor logistic regression is firstly applied to modeling data to construct a prediction model of the ovarian response failure, and the effect of the model is verified in verification data. The performance of the established prediction model was evaluated using measurements of area under the curve (AUC), sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) provided in the software.

First, a multifactorial logistic regression was performed on the modeled data, i.e., 1523 subjects' data, with whether ovarian hypo-reactivity as the outcome variable and AMH, FSH and age as the independent variables, and three continuous variables were converted into categorical variables, three parameters of age, FSH level and AMH level, as shown in table 2, due to the strong correlation between the three independent variables.

TABLE 2 grouping basis

The subject age, AMH and FSH have been converted to multi-categorical variables according to the identified groupings in table 2. The age of the subjects was divided into three groups, respectively: the subject is under 30 years of age, the subject is above 30 years of age and under 40 years of age, and the subject is above 40 years of age. Subjects' anti-mullerian hormone (AMH) levels were divided into five groups, each: the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, the subject's anti-mullerian hormone (AMH) level is above 0.5ng/ml and less than 1ng/ml, the subject's anti-mullerian hormone (AMH) level is above 1ng/ml and less than 1.5ng/ml, the subject's anti-mullerian hormone (AMH) level is above 1.5ng/ml and less than 2ng/ml, and the subject's anti-mullerian hormone (AMH) level is greater than 2 ng/ml. Subject levels of Follicle Stimulating Hormone (FSH) were divided into four groups, respectively: the subject's Follicle Stimulating Hormone (FSH) level is less than 6.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is above 6.5IU/L and less than 8.5IU/L, the subject's Follicle Stimulating Hormone (FSH) level is above 8.5IU/L and less than 10.5IU/L, and the subject's Follicle Stimulating Hormone (FSH) level is above 10.5IU/L, thereby converting age, AMH, and FSH into multi-categorical variables according to the above criteria.

The following formula was fitted and the parameters involved in the formula were confirmed using the data of the training set as shown in table 3:

p ^ 1/(1+ e ^ (a + b ^ age + c ^ FSH + d ^ AMH))) (formula I)

TABLE 3

P is a parameter calculated to characterize ovarian reserve function in the subject as shown in equation one, wherein a, b, c, and d are unitless parameters; wherein, in the module for calculating ovarian reserve function, values of b, c and d are obtained based on the age of the subject, the anti-mullerian hormone (AMH) level of the subject and the Follicle Stimulating Hormone (FSH) level of the subject to be substituted into formula one for calculation, wherein in the calculation, the values of age, FSH and AMH are 0 or 1.

As shown in table 3, one of the parameters involved in the formula is: a is any value selected from-4.072 to-3.188, and a is preferably-3.630; age is 0 when the subject is at age 30 years and below, age is 1 when the subject is at age greater than 30 years and at age 40 years and below, b is any number selected from 0.163-0.960, b is preferably 0.561, and when the subject is at age greater than 40 years, age is 1, b is any number selected from 0.295-1.317, b is preferably 0.806; the FSH is 0 when a Follicle Stimulating Hormone (FSH) level of the subject is less than 6.5IU/L, the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 6.5IU/L or more and less than 8.5IU/L, c is any value selected from 0.239 to 1.006, c is preferably 0.622, the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 8.5IU/L or more and less than 10.5IU/L, c is any value selected from 0.363 to 1.303, c is preferably 0.833, and the FSH is 1 when the Follicle Stimulating Hormone (FSH) level of the subject is 10.5IU/L or more, c is any value selected from 0.847 to 1.712, c is preferably 1.279. When the subject's anti-mullerian hormone (AMH) level is 2ng/ml and above, AMH is 0; when the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, AMH is 1, d is any value selected from 2.708-3.701, d is preferably 3.204, when the subject's anti-mullerian hormone (AMH) level is 0.5ng/ml and above and less than 1ng/ml, AMH is 1, d is any value selected from 1.985-2.887, d is preferably 2.436, when the subject's anti-mullerian hormone (AMH) level is 1ng/ml and above and less than 1.5ng/ml, AMH is 1, d is any value selected from 1.153-2.070, d is preferably 1.612, when the subject's anti-mullerian hormone (AMH) level is 1.5ng/ml and above and less than 2ng/ml, AMH is 1, d is any value selected from 0.230-1.356, d is preferably 0.793.

The data was then validated using 3273 subjects' data from 2018 using the above grouping basis and formula. By verifying as above, it was confirmed that the acquisition of the model constructed as described above could predict well the ovarian reserve function of the subject.

In order to verify the accuracy of the system, the accuracy of the system of the present application and the accuracy of the system of the prior application (CN201811516206.4) evaluated by the same population are evaluated by using the evaluation function of JMP Pro 14.2 software, and as can be seen from the results shown in table 4 below, the system constructed in the present embodiment and the system applied online can reach the same evaluation level.

TABLE 4

Thus, the ovarian hypo-responsiveness of a subject can be calculated based on the age of the subject, the concentration of anti-mullerian hormone at any day of the menstrual cycle, and the concentration of follicle stimulating hormone in the venous blood from 2 to 4 days of menstruation, according to the formula I above.

Grouping the population according to the calculated parameter of the low ovarian response probability, wherein the grouping adopts the grouping standard (see CN201811516206.4) previously confirmed by the applicant, namely when the calculated parameter (p) for representing the low ovarian response probability of the subject is less than 10%, the grouping module determines that the subject belongs to the ovarian reserve and has good function; when the calculated parameter (p) for representing the ovarian hypo-response probability of the subject is less than 25 percent and is less than 10 percent, the grouping module determines that the subject belongs to the ovarian reserve function better; when the calculated parameter (p) for characterizing the ovarian hypo-response probability of the subject is less than 50%, the grouping module determines that the subject belongs to poor ovarian reserve function; when the calculated parameter (p) for representing the low ovarian response probability of the subject is more than or equal to 50 percent, the grouping module determines that the subject belongs to poor ovarian reserve function.

While embodiments of the present invention have been described above, the present invention is not limited to the specific embodiments and applications described above, which are intended to be illustrative, instructive, and not limiting. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto without departing from the scope of the invention as defined by the appended claims.

Claims

1. A system for assessing ovarian reserve function in a subject, comprising:

a module for calculating ovarian reserve function, which is used for calculating the information acquired in the data acquisition module so as to calculate the probability (p) of low ovarian response of the testee;

calculating an ovarian hypo-response probability (p) of the subject using a multi-categorical variable into which data for the subject's age, subject's anti-mullerian hormone (AMH) level, subject's Follicle Stimulating Hormone (FSH) level are converted in a module for calculating ovarian reserve function;

in the module for calculating ovarian reserve function, subject age was converted into three categorical variables, i.e., subject age was divided into three groups, respectively: the subject's age is 30 years and below, the subject's age is greater than 30 years and is 40 years and below, and the subject's age is greater than 40 years;

in the module for calculating ovarian reserve function, the subject's anti-mullerian hormone (AMH) levels are converted into five categorical variables, i.e., the subject's anti-mullerian hormone (AMH) levels are divided into five groups, respectively: (ii) an anti-mullerian hormone (AMH) level of less than 0.5ng/ml in the subject, an anti-mullerian hormone (AMH) level of 0.5ng/ml and above and less than 1ng/ml in the subject, an anti-mullerian hormone (AMH) level of 1ng/ml and above and less than 1.5ng/ml in the subject, an anti-mullerian hormone (AMH) level of 1.5ng/ml and above and less than 2ng/ml in the subject, and an anti-mullerian hormone (AMH) level of greater than or equal to 2ng/ml in the subject;

in the module for calculating ovarian reserve function, the subject's Follicle Stimulating Hormone (FSH) level is converted into four categorical variables, i.e., the subject's Follicle Stimulating Hormone (FSH) level is divided into four groups, respectively: a subject's Follicle Stimulating Hormone (FSH) level of less than 6.5IU/L, a subject's Follicle Stimulating Hormone (FSH) level of more than 6.5 and IU/L and less than 8.5IU/L, a subject's Follicle Stimulating Hormone (FSH) level of more than 8.5IU/L and less than 10.5IU/L, and a subject's Follicle Stimulating Hormone (FSH) level of more than 10.5 IU/L;

a module for calculating an ovarian reserve function, which stores in advance a formula for predicting a low ovarian response probability (p) of a subject, which is based on a multi-classification variable fit to which data on the subject's age, subject's anti-mullerian hormone (AMH) level, and subject's Follicle Stimulating Hormone (FSH) level of the subject are converted in an existing database;

the formula is the following formula one:

p ^ 1/(1+ e ^ (a + b ^ age + c ^ FSH + d ^ AMH))) (formula I)

wherein a, b, c and d are unitless parameters;

2. The system of claim 1, further comprising:

3. The system of claim 2, wherein,

the anti-mullerian hormone (AMH) level refers to the concentration of anti-mullerian hormone in venous blood on any day of the menstrual cycle of the female subject, and the Follicle Stimulating Hormone (FSH) level refers to the concentration of follicle stimulating hormone in venous blood on 2-4 days of menstruation of the female subject.

4. The system of claim 2, wherein,

a is any value selected from-4.072 to-3.188;

when the subject is aged 30 years and below, age is 0,

when the subject is older than 30 years and 40 years and younger, age is 1, b is any number selected from 0.163 to 0.960, and

when the subject is older than 40 years, age is 1, b is any number selected from 0.295-1.317;

when the subject has a Follicle Stimulating Hormone (FSH) level of 6.5IU/L or more and less than 8.5IU/L, the FSH is 1, c is any value selected from 0.239 to 1.006,

when the subject has a Follicle Stimulating Hormone (FSH) level of 8.5IU/L or more and less than 10.5IU/L, the FSH is 1, c is any value selected from 0.363 to 1.303, and

when the subject has a Follicle Stimulating Hormone (FSH) level of 10.5IU/L or above, the FSH is 1, and c is any value selected from 0.847-1.712;

when the subject's anti-mullerian hormone (AMH) level is 2ng/ml and above, AMH is 0,

when the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, AMH is 1, d is any value selected from 2.708-3.701,

when the subject's anti-mullerian hormone (AMH) level is 0.5ng/ml or more and less than 1ng/ml, AMH is 1, d is any value selected from 1.985-2.887,

when the subject's anti-mullerian hormone (AMH) level is 1ng/ml or more and less than 1.5ng/ml, AMH is 1, d is any value selected from 1.153 to 2.070, when the subject's anti-mullerian hormone (AMH) level is 1.5ng/ml or more and less than 2ng/ml, AMH is 1, d is any value selected from 0.230 to 1.356.

5. The system of claim 4, wherein,

a is-3.630;

when the subject is aged 30 years and below, age is 0,

when the subject is older than 30 years and under 40 years, age is 1, b is 0.561, and

age is 1, b is 0.806 when the subject is older than 40 years of age;

when the subject has a Follicle Stimulating Hormone (FSH) level of 6.5IU/L or more and less than 8.5IU/L, the FSH is 1, c is 0.622,

when the subject's Follicle Stimulating Hormone (FSH) level is 8.5IU/L and above and less than 10.5IU/L, the FSH is 1, c is 0.833, and

FSH is 1 and c is 1.279 when the subject's Follicle Stimulating Hormone (FSH) level is 10.5IU/L or greater;

when the subject's anti-mullerian hormone (AMH) level is less than 0.5ng/ml, AMH is 1, d is 3.204,

when the subject's anti-mullerian hormone (AMH) level is 0.5ng/ml and above and less than 1ng/ml, AMH is 1, d is 2.436,

when the subject's anti-mullerian hormone (AMH) level is 1ng/ml and above and less than 1.5ng/ml, AMH is 1, d is 1.612,

when the subject's anti-mullerian hormone (AMH) level is 1.5ng/ml and above and less than 2ng/ml, AMH is 1 and d is 0.793.

6. The system of any one of claims 2 to 5,

the grouping basis prestored in the grouping module is as follows: